Research on Automatic Monitoring in Students’ Abnormal Online Behavior Based on Data Mining
Download as PDF
DOI: 10.23977/ICCIA2020063
Corresponding Author
Shujie Liang
ABSTRACT
With the rapid development of big data technology, the data processing ability of all walks of life has been greatly improved. All walks of life can dig out effective information from the data or analyze abnormal data, conduct detailed analysis and detection, effectively deal with some potential security problems, and ensure the safe operation of the industry. For the management of students’ online behavior, big data technology can help managers collect students’ online behavior data, extract valuable information from the data through a series of algorithms, and identify the students with abnormal behavior, so as to make managers pay more attention to such students. This paper will start from the behavior characteristics of students’ online users, introduce the functions of analysis and monitoring system about network abnormal behavior, and put forward some big data technologies to effectively improve the quality of management.
KEYWORDS
Data mining; Internet access; Abnormal behavior; Automatic monitoring